{"id":"https://openalex.org/W2773759172","doi":"https://doi.org/10.1109/igarss.2017.8127470","title":"A new PolSAR decomposition algorithm to delineate urban targets","display_name":"A new PolSAR decomposition algorithm to delineate urban targets","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2773759172","doi":"https://doi.org/10.1109/igarss.2017.8127470","mag":"2773759172"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2017.8127470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8127470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048924690","display_name":"Dingfeng Duan","orcid":"https://orcid.org/0000-0002-4984-3573"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dingfeng Duan","raw_affiliation_strings":["Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424542","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0003-3366-3137"},"institutions":[{"id":"https://openalex.org/I186335123","display_name":"East Carolina University","ror":"https://ror.org/01vx35703","country_code":"US","type":"education","lineage":["https://openalex.org/I186335123"]},{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["Department of Geography, Planning, and Environment, East Carolina University, Greenville, North Carolina, USA","Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Department of Geography, Planning, and Environment, East Carolina University, Greenville, North Carolina, USA","institution_ids":["https://openalex.org/I186335123"]},{"raw_affiliation_string":"Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101614227","display_name":"Haitao Lv","orcid":"https://orcid.org/0000-0001-8067-4547"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Lv","raw_affiliation_strings":["Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019064751","display_name":"Hong Li","orcid":"https://orcid.org/0000-0002-8117-8980"},"institutions":[{"id":"https://openalex.org/I186335123","display_name":"East Carolina University","ror":"https://ror.org/01vx35703","country_code":"US","type":"education","lineage":["https://openalex.org/I186335123"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Li","raw_affiliation_strings":["Department of Information Management Systems, East Carolina University, Greenville, North Carolina, USA"],"affiliations":[{"raw_affiliation_string":"Department of Information Management Systems, East Carolina University, Greenville, North Carolina, USA","institution_ids":["https://openalex.org/I186335123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091755587","display_name":"Yuanyuan Yang","orcid":"https://orcid.org/0000-0002-8391-2528"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Yang","raw_affiliation_strings":["Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing Big Data, UESTC, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5048924690"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09917065,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":null,"first_page":"2381","last_page":"2384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/azimuth","display_name":"Azimuth","score":0.7466042041778564},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.6824565529823303},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.6479218006134033},{"id":"https://openalex.org/keywords/scattering","display_name":"Scattering","score":0.6407177448272705},{"id":"https://openalex.org/keywords/coefficient-matrix","display_name":"Coefficient matrix","score":0.5744906067848206},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.570431113243103},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.5691214799880981},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4867691993713379},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47285011410713196},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.46429547667503357},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34006452560424805},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32064515352249146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3089245557785034},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.17480292916297913},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1689150333404541},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1276404857635498},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10232263803482056},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09297415614128113},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07399061322212219}],"concepts":[{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.7466042041778564},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.6824565529823303},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.6479218006134033},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.6407177448272705},{"id":"https://openalex.org/C60866291","wikidata":"https://www.wikidata.org/wiki/Q5140577","display_name":"Coefficient matrix","level":3,"score":0.5744906067848206},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.570431113243103},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5691214799880981},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4867691993713379},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47285011410713196},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.46429547667503357},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34006452560424805},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32064515352249146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3089245557785034},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.17480292916297913},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1689150333404541},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1276404857635498},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10232263803482056},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09297415614128113},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07399061322212219},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2017.8127470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8127470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1974024703","https://openalex.org/W2010344121","https://openalex.org/W2097272115","https://openalex.org/W2141424348","https://openalex.org/W2150059023","https://openalex.org/W2162345509","https://openalex.org/W2339432337"],"related_works":["https://openalex.org/W3006474185","https://openalex.org/W2483195039","https://openalex.org/W2281797687","https://openalex.org/W2358411735","https://openalex.org/W2048211457","https://openalex.org/W4250650723","https://openalex.org/W2611761074","https://openalex.org/W2358598243","https://openalex.org/W2331534598","https://openalex.org/W2313632216"],"abstract_inverted_index":{"A":[0],"new":[1,17,66],"four":[2],"component":[3,52],"decomposition":[4,58,68],"algorithm":[5,59,69],"for":[6],"urban":[7,26,89,93],"targets":[8,94],"delineation":[9],"from":[10],"PolSAR":[11],"imagery":[12],"was":[13,20,30,44,70],"studied.":[14],"First,":[15],"a":[16,38,65],"correlation":[18],"coefficient":[19,29,43],"introduced":[21],"to":[22,46],"describe":[23],"characteristics":[24],"of":[25,34,37,77,84],"targets.":[27],"The":[28],"the":[31,42,48,61,73,75,82,92],"linear":[32],"combination":[33],"two":[35],"elements":[36],"coherent":[39],"matrix.":[40],"Then,":[41],"used":[45],"modify":[47],"volumetric":[49,85],"scattering":[50,79,86],"model":[51],"in":[53,88],"Yamaguchi":[54],"et":[55],"al.'s":[56],"four-component":[57,67],"with":[60],"azimuth":[62,96],"deorientation.":[63],"Thus,":[64,91],"established.":[71],"With":[72],"algorithm,":[74],"percentage":[76,83],"double-bounced":[78],"increased":[80],"but":[81],"decreased":[87],"areas.":[90],"whose":[95],"angles":[97],"are":[98],"0\u00b0":[99],"or":[100],"non-zero\u00b0":[101],"were":[102],"effectively":[103],"identified.":[104]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}